Update app.py

app.py

@@ -1,32 +1,70 @@
-# app.py
 import os
 import gradio as gr
-import google.generativeai as genai
-
-# Configure the Gemini client using an environment variable
-genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
-
-# Create the model and start a stateful chat session
-model = genai.GenerativeModel("gemini-2.0-flash")
-chat = model.start_chat(history=[])
-
-# Define the function that Gradio will call on each user message
-def respond(message, history):
-    # Send the user's message to the chat session
-    response = chat.send_message(message)
-    # Return only the model's text response
-    return response.text
-
-# Build the Gradio UI
-# The retry_btn, undo_btn, and clear_btn arguments have been removed
-# as this functionality is now integrated into the Chatbot component.
-iface = gr.ChatInterface(
-    fn=respond,
-    title="Gemini Chatbot",
-    chatbot=gr.Chatbot(height=600, type="messages"),
-    textbox=gr.Textbox(placeholder="Ask anything…", container=False, scale=7),
-)
-
-# Launch the application
-if __name__ == "__main__":
-    iface.launch()
+import requests
+import importlib.util
+from pathlib import Path
+
+# Define the model files content
+model_files = {
+    "gpt5_model.py": """
+class GPT5Model:
+    def __init__(self, api_key):
+        self.api_key = api_key
+        self.system_prompt = "You are GPT-5, the most advanced AI model available. Answer accurately, intelligently, and helpfully."
+
+    def generate_response(self, prompt):
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json"
+        }
+        full_prompt = f"{self.system_prompt}\\nUser: {prompt}\\nGPT-5:"
+        data = {
+            "prompt": full_prompt,
+            "max_tokens": 150
+        }
+        import requests
+        response = requests.post("https://api.pplx.ai/v1/generate", json=data, headers=headers)
+        return response.json()["choices"][0]["text"].strip()
+    """,
+    "gpt5_utils.py": """
+def load_model(api_key):
+    from gpt5_model import GPT5Model
+    return GPT5Model(api_key)
+    """
+}
+
+# Write the model files to disk
+for filename, content in model_files.items():
+    Path(filename).write_text(content.strip())
+
+# Import the load_model function dynamically
+spec = importlib.util.spec_from_file_location("gpt5_utils", "gpt5_utils.py")
+gpt5_utils = importlib.util.module_from_spec(spec)
+spec.loader.exec_module(gpt5_utils)
+
+# Get API key from environment
+api_key = os.getenv("PPLX_API_KEY")
+if not api_key:
+    raise ValueError("API key not found. Please set PPLX_API_KEY environment variable.")
+
+# Load the GPT5 model
+model = gpt5_utils.load_model(api_key)
+
+# Response generation function
+def generate_response(prompt):
+    if len(prompt) > 1:
+        return "Error: Prompt must be exactly 1 character long."
+    return model.generate_response(prompt)
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# GPT5 Model Interface")
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Enter your prompt (1 character only)", placeholder="Enter a single character")
+            generate_btn = gr.Button("Generate Response")
+            output = gr.Textbox(label="Generated Response")
+
+    generate_btn.click(generate_response, inputs=prompt, outputs=output)
+
+demo.launch()